In this paper, a research is implemented on the adversarial example attack and neural network interpretability. The neural network interpretability research is believed to have considerable potential in resistin
We retrieve K′ = cK examples, where c ≫ 1, and uniformly se- lect K examples at random to form a feature-space convex hull. We evaluate this approach later against the strongest attack [5]. 2.2. Training The output of the classifier g(P(x)) is...
(a) Testing accuracy of ResNet50 under the white-box attack; (b) Feature distances of ResNet50 under the white-box attack between the inputs (original and preprocessed images) and their adversarial examples. (c) Testing accuracy of ResNet50 on transferable adversarial examples; (d) Feature ...
All images are pre-processed with mean and std of the ImageNet dataset before being fed to the model. None of the code uses GPU as these operations are quite fast (for a single image). You can make use of gpu with very little effort. The examples below include numbers in the brackets...
Convolutional neural network (CNN), a class of artificial neural networks that has become dominant in various computer vision tasks, is attracting interest across a variety of domains, including radiology. CNN is designed to automatically and adaptively learn spatial hierarchies of features through back...
Illustration of the proposed replay attack detection neural network. The dark rectangle represents variable convolution, and the three internal parameters refer to the parameters of the CNN layer on the right side of Figure 2. First, the convolution kernel size is set to 5 by 5, and the step...
Journal of Intelligent Systems 2023; 32: 20220265 Research Article Dang-en Xie, Hai-na Hu, and Qiang Xu* Replay attack detection based on deformable convolutional neural network and temporal-frequency attention model https://doi.org/10.1515/jisys-2022-0265 received November 14, 2022; accepted ...
A Convolutional Neural Networks Introduction so to speak. Step 1: Convolution Operation The first building block in our plan of attack is convolution operation. In this step, we will touch on feature detectors, which basically serve as the neural network's filters. We will also discuss feature ...
Abstract Nowadays, convolutional neural network (CNN) based steganalysis methods achieved great performance. While those methods are also facing security problems. In this paper, we proposed an attack scheme aiming at CNN based steganalyzer including two different attack methods 1) the LSB-Jstego Gradi...
Air quality monitoring Belief Rule Based Expert System (BRBES) Convolutional Neural Network (CNN) Uncertainty 1. Introduction Air pollution, a critical environmental problem, is under increasing global focus (Li, Xie, Ren, Guo, Yang, & Xu, 2020). Presently, air pollution is the fourth most se...